This invention relates to the field of technical reproduction of graphical images. In particular it relates to a hyperspectral system for measuring and transforming light from individual pixel elements, or pixels, that comprise an image, into a standardized representation where each pixel""s notation is a location in a perceptual color space defined by the Commission Internationale de l""Eclairage (CIE).
Conventional apparatus for capturing colored graphical images utilize a method based upon an industrial implementation of a central color science concept, the Trichromatic Generalization, which explains how colors mix and match. In the conventional scheme, a coordinate system characterized as a Device Dependent Color Space (DDC) utilizes linear mixtures of three arbitrary primary colors to match the color of individual pixels of the original.
Color Science evolved over more than 300 years of experimentation and observation and is called colorimetry. A complete review of colorimetry or the specification of human color perception is beyond the scope of this document. However, key physiological, physical and psychological factors central to determining any calorimetric system""s accuracy and precision are reviewed.
The origin of the scientific Trichromatic Generalization has its basis in human physiology. The sensation of color is a complex interaction of the human nervous system with light, electromagnetic radiation found between the wavelengths of 300 nm and 830 nm (as illustrated by FIG. 1). Ordering the psychological designations of color perception creates the visible spectrum, from short to long wavelengths, violet, blue, green, yellow, orange, and red. The color matching rules of the Trichromatic Generalization are used to predict how mixtures of the different wavelengths are perceived by humans. Complicating the mechanical aspects of color perception are visual system anomalies.
The human eye""s lens brings different wavelengths of light to focus at different distances behind the lens and absorbs almost twice as much blue light as yellow or red, resulting in a relative insensitivity to shorter wavelengths, a condition exaggerated by age. The light that finally passes through the eye strikes the retina, a small area at the back of the eye densely packed with individual light sensitive receptors connected to the optic nerve, the conduit that transmits and processes visual sensations from the eye to the visual cortex in the brain. It has been shown the light sensitive photoreceptors are of two kinds, rods, which function at night or at very low light levels, and cones, which function under daylight conditions and are the sole source of color perception sensations in humans. The cones are circularly situated at the center of the eye""s focal area, the fovea, with the rods forming a ring around the cones.
The notion of xe2x80x9ctrixe2x80x9d associated with the Trichromatic Generalization arises from the relative sensitivity of the three different cone types generally accepted to be found within the fovea. About 64% of cones exhibit peak sensitivity to 575 nm wavelength light and are said to be red sensitive, though the 575 nm bandpass is actually perceived as yellow. Thirty two percent of cones are considered green, most sensitive to 535 nm light, and only two percent are blue, having a peak response at about 445 nm. It is generally believed analyzing the ratio of the neural activities generated by visually stimulating the three different photoreceptors is the method by which the human visual system interprets color. In practice, it has been shown that the channels of information from the three cones are transformed into three new so-called opponent channels, transmitting a red to green ratio, a yellow to blue ratio and a brightness factor, based upon red and green only, to the brain""s visual cortex (as illustrated in FIG. 2). The physiological sensations produced by visual stimulus is thought to be correlated with stored psychological perceptions, creating color vision.
The above described physiology allows perception of the physical aspects of color, electromagnetic radiation found between the wavelengths of 380 nm and 780 nm, referred to here as human-visible light. Physically, color perception varies according to the wavelength of the visual stimulus. Wavelength is calibrated in nm (nanometer) denominated units, with groups or multiple wavelengths described as bandwidth. When the bandpass of the bandwidth is narrow, the resulting perceptions are associated with pure, or highly saturated, color. As the observed bandpass widens, the color appears less pure. Observers with normal color vision generally identify pure blue as light with a wavelength of about 470 nm, pure green as light with a wavelength of about 505 nm, pure yellow as 575 nm light, and pure red as 610 nm light. However, individual observers often respond differently to the same specimen, so what is a pure color to one may not be perceived that way by another observer.
Besides wavelength, other important physical attributes of visible light are luminance, illuminance, transmittance (reflectance) and metamerism. Luminance accounts for light emitted, such as from a computer display, calibrated in units that reflect the eye""s uneven sensitivity to different wavelengths. Illuminance is a measurement of the amount of light that falls on an observed object and transmittance (reflectance) is the measurement of light photons that are absorbed and regenerated as new photons in proportion to the amount of original photons that transmitted through (reflected off) the surface of the object. Various wavelengths of light that are absorbed and retransmitted through (reflected off) a measured image (or specimen) and presented as a percentage of the wavelengths of light that initially struck it can be described as the image""s (specimen""s) characteristic spectral transmittance (reflectance) curve (for example, as illustrated by FIG. 3), and plotting and transforming this curve for the purpose of matching colored specimens is a basic aspect of colorimetry. For brevity, we will hereforward refer to transmittance and reflectance simply as transmittance.
It is useful to consider that the reproduction of a colored image may be thought of as an exercise in color matching which takes into account the spectral power distribution of the light source (ie: viewing conditions) illuminating the original, the characteristic curve of the original, the power distribution of the light source illuminating the reproduction, and the characteristic curve of the reproduction. When the characteristic curve of the source""s power distribution is combined with the spectral transmittance of the specimen, a visual stimulus is created which triggers color perception. Mathematically characterizing the color perception triggered by the combination of a source""s power distribution and a specimen""s transmittance curve is a necessary first step in successfully reproducing the perception.
There is, however, a phenomenon that impacts color perception and therefore color reproduction; metamerism. To illustrate the phenomenon, consider two specimens with identical characteristic curves. They will appear to the average observer to match under any source of illuminance. Now, consider two specimens with different curves. They will appear to vary with regards to one another as the source of the illumination is varied. However, there can be two specimens that appear to match despite having different characteristic curves. This is metamerism. An example of metamerism is when the two specimens with different characteristic curves are observed under different sources of illumination, and a match is observed under one of the sources (as illustrated, for example, in FIG. 4). Because the reproduction of colored images entails taking into account different viewing conditions and media, the mathematical characterization of a color perception destined for reproduction must take into account metameric matches. A color measurement system capable of identifying and predicting metamerism is the CIE system (devised by the Commission Internationale de l""Eclaimage), and its mathematical model will be described below.
The above described physiological and physical attributes of color are considered the objective factors effecting color perception and, hence, color reproduction. There are also subjective psychological factors to consider, the most important one being hue. Hue is associated with the wavelength of a visual stimulus, though hue can not be directly measured, as can the stimulus"" wavelength. Psychological hue is comprised of the names of the colors of the visible spectrum. Two human observer""s past experiences with colors and color names would allow them to agree a particular visual stimulus was, for example, blue, but disagree regarding which of a multitude of blue stimuli was the xe2x80x9cbluest.xe2x80x9d
Hue exhibits a non-linear characteristic known as saturation, which is associated with the bandwidth of the visual stimulus, and was previously described as color purity. Different hues of equal bandwidth do not appear to an observer to be equally saturated. And a hue can be desaturated by mixing it with a neutral hue such as white or gray, or with an opponent color.
Another non-linear psychological factor of hue is described as lightness, which scales hue from dark to light and is associated with a specimen""s ability to transmit light. The more light a specimen""s surface transmits, the lighter its hue appears. Brightness is the psychological factor of hue which scales hue from bright to dark and is associated with the intensity of the light source illuminating the specimen. Brightness and the previously described luminance are both associated with the perceived effects of light intensity, but brightness is a perceptual experience while luminance is a measurement modeled mathematically by the so-called luminance efficiency function defined by the CIE. This function describes the eye""s sensitivity to wavelength (as illustrated, for example, by the graph of FIG. 5).
Two final psychological phenomena especially of concern in formal color matching are color constancy, or the preservation of perceived hue relationships despite changes in viewing conditions, and color contrast, or the shifting of perceived hue caused by adjacent hues.
The above described physiological, physical and psychological factors must be accounted for in any system purporting to be a meaningful model of color and by extension, a useful model upon which to base a system for graphical imaging.
Color models mathematically correlate physiological sensations of color perceived by the human eye by assuming that human perception of the color of any pixel in an image may be quantified by three numbers. These numbers are the intensity of three primary color sources whose outputs either (a) overlap to match the pixel color, or (b) two of whose outputs overlap to match the color of the pixel which is itself overlapped by the third primary output. The former case is described as the pixel color equaling a sum of the three primary color outputs; the latter case is described as the color of the pixel matching a sum of the two primary outputs minus the third primary output.
The three primary colors forming the basis for quantifying colors are not unique. They may be chosen almost arbitrarily, the important points being that three suffice and none of the primary stimuli can be color matched by a mixture of the other two. The three primary colors may be considered to form a color model, a basis in a three dimensional linear vector space. A different set of three primary colors is simply a different basis within the linear color space. The coordinates of a color in a model with respect to each basis are simply the intensities of the basis primary colors whose superposition (positive or negative) matches the color. The Trichromatic Generalization assumes linear transformations suffice to describe a change in intensity and all device dependent color models are linear. However, the CIE system includes non-linear color model transformations and procedures to account for different viewing conditions and visual phenomena such as metamerism and color contrast. And, to simplify color matching, the CIE system uses mathematical means, imaginary primaries designated X, Y and Z, to eliminate color matching possibilities that require a minus primary value to make a match. The X, Y and Z primaries create a superset of color which includes all colors a human might perceive. This is a key difference as compared to the physical primaries integrated into current graphical imaging systems, whose color gamut (or range of producible colors) is a subset of human color perception.
The three primary colors X, Y and Z utilized by the device independent CIE color model are mathematical abstractions based upon statistical analysis of the response of different observers to color specimens compared in a highly standardized manner. For example, the CIE has defined a standard manner for observing a color match which requires observing a structure free specimen field that subtends 2xc2x0 of arc when positioned 45 cm (18 inches) from the eye""s iris. By correlating the results of these observations with precise and accurate measurements of a visual stimuli""s physical color properties, a device independent system able to correctly measure human color perception is created.
Devices currently utilized to quantify color for reproduction means use color systems that require actual samples of real primary colors (usually red, green and blue, i.e. R, G, B) be present to make measurements. Light is transmitted through a colored object and through filters that isolate the primary colors. Upon exiting the primary filters the light, effected by the optical density and color of the object, as well as the three primary color filters, is measured and noted as three integer values, one each for the R, G and B primary component created by the device for the object measured. This method creates a measurement process tied to a specific physical color space, with all the inherent color gamut limitations of physical rather than imaginary primaries. The methods and techniques used to create and measure the R, G and B components of a physical color space vary from vendor to vendor and are without any common standards.
Although a convenient way to describe colors, the limitation of any device dependent system is that regardless of how the three primary colors are chosen, observer metamerism effects (where two objects appear to some observers or devices to have the same color, but to other observers or devices the same objects do not match) cannot be eliminated. Values expressed by a device dependent color system are accurate only within a truncated color space and only if the exact same filters, lights, inks or pigments used to render a particular color are used as the physical primaries in the measuring device, which is an impossibility. That being the case, it has been recognized that more information than is contained in a device dependent color model is needed to produce accurate color reproduction.
Despite it""s known inaccuracy, device dependent color-based measuring and rendering systems have been integrated into virtually all industrial and commercial applications related to the processes that are called upon to reproduce full color images, such as printing, photography and television. Over generations the conflict of accurately measuring and rendering with physical color systems has lead to extensive trade practices being established. These practices, commonly referred to as xe2x80x9ccolor correction,xe2x80x9d integrate human judgment with the physical color systems in a way that requires humans to make decisions to resolve or mask the inherent limitations of a physical color system. In physical color image scanning methods, humans are expected to compensate for differences between the color content of the original image, what a scanner can capture of the original color content, how the scanner describes what it captured, and how the captured data must be adjusted for use by various digital, xerographic and lithographic rendering processes.
There exist however sophisticated quantitative parameterizations of color that are available to improve the process for color reproduction. Two such standards are 1) the ASTM (American Society for Testing and Materials, West Conshohocken, Pa.) standards E 1164-94, Standard Practice for Obtaining Spectrophotometric Data for Object-Color Evaluation, and E 308-95, Standard Test Method for Computing the Colors of Objects by Using the CIE System, and 2) the CIE (Wien, Austria) standards CIE 15.2-1986, Colorimetry, 2nd Edition (ISBN 3 900 734 00 3), and ISO/CIE 10526: Colorimetric Illuminants and ISO/CIE 10527: Colorimetric Observers. The ASTM standard is a truncated variation of the CIE standard, which decomposes a color into saturated monochromatic components of known bandwidth, applies mathematical operators to each component and integrates the result to arrive at a set of values characterizing the color.
The ASTM standard, in turn, is the basis for a third, even more abridged graphic arts standard for measuring individual color specimens, CGATS.5-93, Spectral Measurement and Colorimetric Computation for Graphic Arts. The standard is published by The Committee for Graphic Arts Technologies Standards, a group accredited by the Image Technology Standards Board, ITSB, of ANSI, and closely associated with the Working Groups of ISO/TC130 (CGATS, c/o NPES, Reston, Va.).
By agreement, the CIE, (Commission Internationale de l""Eclairage), since 1913, has developed standards regarding how the Trichromatic Generalization is interpreted, as well as how color is measured and described. The underlying premise of the CIE system, referred to as CIE-31, is that the stimulus for color is provided by the proper combination of a source of light, an object, and an observer. In 1931 the CIE introduced standardization of the source and observer and the methodology to derive numbers that provide a measure of a color seen under a standard source of illumination by a standard observer (source and observer models are respectively illustrated by FIGS. 6, 7). This standardization forms the foundation of modern colorimetry. CIE-31 uses a specimen""s Characteristic Curve for the calculation of Tristimulus Values X, Y, and Z and Chromaticity Coordinates x and y. The CIE-76 recommendations establish transformations of the X, Y, and Z Tristimulus Values into nearly visually uniform color scales such as CIELAB, and also established a method to quantify differences between two color specimens.
Chromaticity Coordinates x and y are the result of linear transforms of X, Y and Z and, when plotted, locate visible colors in a two-dimensional horseshoe-shaped graph representing the CIE 1931 xyY color space. While only two of the three dimensions of color are shown on a Chromaticity Diagram (see FIG. 8), a three-dimensional version of the diagram is often made by plotting an axis for Y rising from the illuminant point of the diagram (see FIG. 9).
CIELAB (L*a*b*), the result of a non-linear transformation of X, Y and Z, is an opponent-type system that assumes a color cannot be red and green at the same time, or yellow and blue at the same time, though it can be both red and yellow (ie: orange) or red and blue (ie: purple). Therefore, a specimen""s redness or greenness can be expressed as a single number, called a*, which is positive if the color is red and negative if it is green. It follows that yellowness or blueness is designated by the coordinate b*, positive for yellow and negative for blue. The third coordinate, L*, is the lightness of the color. The CIELAB color space (as illustrated by FIG. 10) is expressed graphically by plotting in rectangular coordinates the quantities L*a*b*.
The full benefit of the CIE system has not been taken advantage of by the graphic arts industry with regards to image scanning. Even manufacturers of printing inks, photographic dyes and color monitors for computers and televisions utilize ASTM-based standards, not the more complex and exact CIE standards.
The less stringent ASTM industrial standards for color measurement truncate the wavelength range between 360 nm and 780 nm and support bandpasses of 10 nm and 20 nm for a variety of illuminants. The least stringent standard for color measurement, CGATS.5-93, also truncates its spectrum between 360 nm and 780 nm, and supports only 10 nm and 20 nm wide bandpasses for one type of illuminant. Devices capable of measuring 1 nm and 5 nm wide bandpasses of radiant energy are sometimes referred to as hyperspectral in the literature, while devices capable of measuring 10 nm or 20 nm wide bandpasses of radiant energy are referred to as multispectral devices.
To summarize, at this time commercially available Trichromatic color image scanners generally employ device-dependent color (DDC) densitometry techniques. Examples of such conventional systems include, for example, Agfa Corp.""s (Ridgefield Park, N.J.) AgfaScan T5000 Plus, Heidelberg USA""s (Kennesaw, Ga.) Primescan D8400, Creo Americas, Inc.""s (Bedford, Mass.) EverSmart Supreme, and Imacon, Inc.""s (Redmond, Wash.) Flextight 848.
A device disclosed in U.S. Pat. No. 5,319,472, issued Jun. 7, 1994 and hereby incorporated by reference, describes an abridged spectrophotometer for image capture. This system utilizes interference filters to separate light into overlapping bands of radiant energy. These bands, which span a truncated portion of the spectrum usually associated with human color perception, are too wide to comply with the aforementioned scientific and industrial standards. The results of such scanning may be notated using the mathematical aspects of the CIE""s spectrophotometric system, but such data can only indirectly, and with limited accuracy, be in agreement with actual CIE-compliant, hyperspectrally observed data.
Accordingly, it would be desirable for a graphical image scanner to be configured for capturing colored images in accordance with scientific, device-independent colorimetry standards that are compliant with international standards such as CIE-31 and CIE-76.
A novel method and apparatus is disclosed for creating a master of a graphical image in accordance with scientific, device independent colorimetry standards (here, the term xe2x80x9cmasterxe2x80x9d is used to connote a highly accurate and pure representation of the image). A graphical image scanner according to the present invention comprises a light source to illuminate the graphical image, a collector to segment the image into a plurality of pixels and collect light emanating from the plurality of pixels, a hyperspectral analyzer to divide the collected light into a plurality of hyperspectral bandpasses and measure a light intensity for each of the hyperspectral bandpasses, a calculator to transform the measured light intensities for the plurality of hyperspectral bandpasses into a device-independent representation of color for each of the pixels, a processor with stored program control to format the device-independent color representations for the plurality of pixels as a digital data file, and a memory for storing the digital data file. The hyperspectral bandpasses define a continuous spectrum characterized by wavelengths ranging between 360 and 830 nanometers, in accordance with color measurement standards established by the Commission Internatonale de l""Eclairage (CIE). Each hyperspectral bandpass is characterized by a substantially unique and non-overlapping selection of continuous wavelengths from the spectrum. The light intensities for the hyperspectral bandpasses are transformed using CIE-devised parameters and algorithms to produce a device-independent color representation for each pixel in the graphical image.